Syed Ahmed Husaini

Designed and deployed a FastAPI-based round-robin agent assignment engine with tiered eligibility logic (segment, specialism, location fallback) and persistent state management, replacing manual ticket routing. Built a configurable lead-scoring driving automated qualification and prioritization of inbound sales tickets Engineered 10 production n8n workflows integrating Freshdesk, SharePoint, and Outlook overing ticket lifecycle automation, geo-based routing, reminder scheduling, and data export.

Architected Kafka-based real-time streaming for Shopify, Freshsales, and JTL ecosystems. Deployed ML recommendation engines and customer segmentation to drive e-commerce growth. Automated core business processes using self-hosted n8n, significantly reducing manual sales overhead. Spearheaded the full data lifecycle—from high-volume API ingestion to centralized PostgreSQL datasets. Consulted for Sales/Ops leads to translate data insights into inventory optimization strategies.

- Price Optimization using Demand forecasting and Mixed Integer Programming. - Forecasting Models include ( Regressor Models , LSTM) - Optimize using Gurobi Optimizer and OR-tools (CP Model) - Also applied Deep Reinforcement Learning Approach (DQN)

Worked on O2O project for Daimler AG: I was responsible for the development of Recommendation engine of one existing vehicle configuration to recommend additional options to users based on Item similarity using Neural Networks.

My job is to create presentations into Latex and modify them according to given requirements.

Asp.net Developer and database developer ( Tools: Visual studio,SQL SERVER)

Major Courses: Machine Learning, Big Data Analytics, Business Analytics, Deep Learning, Distributed Data Analytics, Planning and Optimal Control